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Converting WinBUGS model
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Saeed Siam  
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 More options Jun 20 2010, 6:27 pm
From: Saeed Siam <saeed.s...@gmail.com>
Date: Sun, 20 Jun 2010 15:27:25 -0700 (PDT)
Local: Sun, Jun 20 2010 6:27 pm
Subject: Converting WinBUGS model
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Hi,

I am new to PyMC. For starting, I was trying to convert WinBUGS <a
href="http://users.aims.ac.za/~mackay/BUGS/Examples/Eyes.html"> Eyes
example </a> to PyMC.

I have assumed that Categorical() in the PyMC is equivalent the
WinBUGS' dcat(), So for the following WinBUGS model,

   model
   {
      for( i in 1 : N ) {
         y[i] ~ dnorm(mu[i], tau)
         mu[i] <- lambda[T[i]]
         T[i] ~ dcat(P[])
      }
      P[1:2] ~ ddirch(alpha[])
      theta ~ dnorm(0.0, 1.0E-6)I(0.0, )
      lambda[2] <- lambda[1] + theta
      lambda[1] ~ dnorm(0.0, 1.0E-6)
      tau ~ dgamma(0.001, 0.001) sigma <- 1 / sqrt(tau)
   }

I have done similar to <a href="http://pastebin.com/GXwLs5bC">this </
a>. But it raises pymc.Node.ZeroProbability exception with the
message  "Stochastic T_1's value is outside its support,
 or it forbids its parents' current values."

I would really appreciate if you can point out what I am doing wrong.

regards,
Saeed


 
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John Salvatier  
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 More options Jun 21 2010, 3:08 am
From: John Salvatier <jsalv...@u.washington.edu>
Date: Mon, 21 Jun 2010 00:08:53 -0700
Local: Mon, Jun 21 2010 3:08 am
Subject: Re: [pymc] Converting WinBUGS model
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I have not gone through all your code yet, but the main difference between
how you would code a BUGS model and a PyMC model relevent to your model is
that in PyMC is that you should vectorize your model. Instead of looping
through your variables, you should create arrays of variables and give those
as arguments to other parts of your model.

For example, instead of your second loop, you should do something like:

    T = pymc.Categorical('T', p=p1,p2)
    mu = pymc.Deterministic(eval=lambda t=T,lambda_0=lambdas[0],
lambda_1=lambdas[1]: t < 0.5 & lambda_0 | lambda_1,
            name='mu')

    Y = pymc.Binomial('Y', n=mu, p=tau, value=y_data, observed=True)

(note that numpy arrays sadly do not work with the 'and' and 'or' operators.
You must use & and | or use the functions.
PyMC *should* be able to deal with how you have written you model, but it is
not how PyMC is meant to be used so it will be harder to debug your model.
PyMC should also normally be able to deal with natural expressions of your
variables to create deterministics, but I am not certain whether this works
with the & and | operators. For example, you might try,

mu = T < .5 & (lambdas[0]  |  lambdas[1])

However, I am not 100% certain that will work (some of the operators might
not be implemented).

I also notice you have the expression "tau**(-1/2)" in your program.
Unfortunately Python does integer division for 1/2 so this will evaluate as
-1 (this will be fixed soon), so use tau**(-.5)  or just sigma = tau **-.5.

I am not certain what your specific error is due to.

John


 
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John Salvatier  
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 More options Jun 21 2010, 3:15 am
From: John Salvatier <jsalv...@u.washington.edu>
Date: Mon, 21 Jun 2010 00:15:56 -0700
Local: Mon, Jun 21 2010 3:15 am
Subject: Re: [pymc] Converting WinBUGS model
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That particular error means that the value of parameters of T are invalid
for a Categorical distribution. "parents" refers to the parameters of the
distribution or deterministic. Can you look at prior.value[0] and
prior.value[1]?

John

On Mon, Jun 21, 2010 at 12:08 AM, John Salvatier
<jsalv...@u.washington.edu>wrote:


 
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